Literature DB >> 24926551

Multiplexed molecular profiling of lung cancer using pleural effusion.

Hiroaki Akamatsu1, Yasuhiro Koh2, Hirotsugu Kenmotsu3, Tateaki Naito3, Masakuni Serizawa4, Madoka Kimura5, Keita Mori6, Hisao Imai3, Akira Ono3, Takehito Shukuya7, Tetsuhiko Taira3, Haruyasu Murakami3, Yasuhisa Ohde8, Masahiro Endo9, Takashi Nakajima10, Toshiaki Takahashi3, Nobuyuki Yamamoto11.   

Abstract

INTRODUCTION: Pleural effusion is frequently observed in patients with advanced lung cancer. Although effusion can be obtained less invasively and repeatedly, its use in multiplexed molecular profiling has not been fully investigated.
METHODS: Between July 2011 and April 2013, pleural effusion samples were obtained from patients with lung cancer at Shizuoka Cancer Center. They were analyzed for EGFR, KRAS, BRAF, PIK3CA, NRAS, MEK1, AKT1, PTEN, and HER2 mutations, EGFR, MET, FGFR1, FGFR2, and PIK3CA amplifications, and ALK, ROS1, and RET fusion genes using pyrosequensing and/or capillary electrophoresis, quantitative reverse-transcriptase polymerase chain reaction, and reverse-transcriptase polymerase chain reaction, respectively.
RESULTS: One hundred and two samples from 84 patients were analyzed. Adenocarcinoma was the most common histological subtype (82%). Genetic abnormalities were detected in 42% of patients. The most common abnormality was EGFR mutation (29%), followed by EML4-ALK rearrangement (5%), KRAS mutation, and EGFR amplification (4%, each). Concordance rates between pleural effusion and matched formalin-fixed, paraffin-embedded samples were 88%. Among 11 patients who provided samples at multiple time points, changes in molecular profile over the course of treatment were observed in five patients.
CONCLUSIONS: The use of pleural effusion for multiplexed molecular testing and real-time monitoring in lung cancer was demonstrated.

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Year:  2014        PMID: 24926551     DOI: 10.1097/JTO.0000000000000203

Source DB:  PubMed          Journal:  J Thorac Oncol        ISSN: 1556-0864            Impact factor:   15.609


  10 in total

1.  ALK gene expression status in pleural effusion predicts tumor responsiveness to crizotinib in Chinese patients with lung adenocarcinoma.

Authors:  Zheng Wang; Xiaonan Wu; Xiaohong Han; Gang Cheng; Xinlin Mu; Yuhui Zhang; Di Cui; Chang Liu; Dongge Liu; Yuankai Shi
Journal:  Chin J Cancer Res       Date:  2016-12       Impact factor: 5.087

2.  Evaluation of liquid based cytology in detection of EGFR mutation in NSCLC by large samples.

Authors:  Zhengwei Dong; Ziyang Cao; Wei Wu; Liping Zhang; Likun Hou; Wei Zhang; Chunyan Wu
Journal:  J Thorac Dis       Date:  2020-09       Impact factor: 2.895

3.  Effective assessment of low times MET amplification in pleural effusion after epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) acquired resistance: Cases report.

Authors:  Chang-Guo Wang; Da-Xiong Zeng; Jian-An Huang; Jun-Hong Jiang
Journal:  Medicine (Baltimore)       Date:  2018-01       Impact factor: 1.889

4.  Malignant pleural effusion supernatant is an alternative liquid biopsy specimen for comprehensive mutational profiling.

Authors:  Zhihua Guo; Zhanhong Xie; Huifang Shi; Wei Du; Lijun Peng; Wei Han; Feidie Duan; Xin Zhang; Mingyan Chen; Junli Duan; Jing Lin; Xuewei Chen; Analyn Ang Lizaso; Han Han-Zhang; Jianxing He; Weiqiang Yin
Journal:  Thorac Cancer       Date:  2019-02-18       Impact factor: 3.500

5.  Detecting EGFR mutations and ALK/ROS1 rearrangements in non-small cell lung cancer using malignant pleural effusion samples.

Authors:  Yi Yao; Min Peng; Qinglin Shen; Qinyong Hu; Hongyun Gong; Qingqing Li; Zhongliang Zheng; Bin Xu; Yingge Li; Yi Dong
Journal:  Thorac Cancer       Date:  2018-12-19       Impact factor: 3.500

6.  Targeted deep sequencing from multiple sources demonstrates increased NOTCH1 alterations in lung cancer patient plasma.

Authors:  Yuwei Liao; Zhaokui Ma; Yu Zhang; Dan Li; Dekang Lv; Zhisheng Chen; Peiying Li; Aisha Ai-Dherasi; Feng Zheng; Jichao Tian; Kun Zou; Yue Wang; Dongxia Wang; Miguel Cordova; Huan Zhou; Xiuhua Li; Dan Liu; Ruofei Yu; Qingzheng Zhang; Xiaolong Zhang; Jian Zhang; Xuehong Zhang; Xia Zhang; Yulong Li; Yanyan Shao; Luyao Song; Ruimei Liu; Yichen Wang; Sufiyan Sufiyan; Quentin Liu; Gareth I Owen; Zhiguang Li; Jun Chen
Journal:  Cancer Med       Date:  2019-08-01       Impact factor: 4.452

7.  Deep convolutional neural network-based classification of cancer cells on cytological pleural effusion images.

Authors:  Xiaofeng Xie; Chi-Cheng Fu; Lei Lv; Qiuyi Ye; Yue Yu; Qu Fang; Liping Zhang; Likun Hou; Chunyan Wu
Journal:  Mod Pathol       Date:  2022-01-10       Impact factor: 8.209

8.  Evaluation of pleural fluid cytology for the diagnosis of malignant pleural effusion: a retrospective cohort study.

Authors:  Lorna Pairman; Lutz E L Beckert; Mark Dagger; Michael J Maze
Journal:  Intern Med J       Date:  2022-04-07       Impact factor: 2.611

9.  Multiplexed molecular profiling of lung cancer with malignant pleural effusion using next generation sequencing in Chinese patients.

Authors:  Xingya Ruan; Yonghua Sun; Wei Wang; Jianwei Ye; Daoyun Zhang; Ziying Gong; Mingxia Yang
Journal:  Oncol Lett       Date:  2020-03-05       Impact factor: 2.967

10.  Detection of ALK Gene Rearrangement in Cell-free RNA from Lung Cancer Malignant Pleural Effusion.

Authors:  Mingliang Chu; Yanqiu Zhu; Jianjun Hu; Zhuxue Zhang; Meng Luo; Xiaobo Ma
Journal:  Biomed Res Int       Date:  2020-01-21       Impact factor: 3.411

  10 in total

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